Course SCI102
Advanced Data Visualisation with Python
Advanced Data Visualisation with Python
Duration: 2 Days
Synopsis
This course provides an intensive overview of Python based 2D, 3D and interactive data visualisation.
Prerequisites
- Attendees are expected to be reasonably experienced Python programmers, and to have a reasonable knowledge of mathematics underlying data visualisation.
Course Outline
Data visualisation and Matplotlib
- Boxplots and Whisker plots
- Scatterplots
- Pie charts
- Subplots
Enthought Traits package
- The traits concept - rationale and motivation
- Validation
- Initialization
- Notification in Traits - Static and Dynamic
- The Traits UI
- Default UI (edit_traits)
- Extending the UI with Views, Groups, and Items
- Trait editors - an overview
- View, Group and Item cutomisation
- Buttons, Menus and Toolbars
- Drag and drop
Enthought 2D and 3D visualisation tools - by example
- Kiva - a display-pdf drawing layer.
- Enable - an object "canvas" layer that abstracts user-event handling
- The array interface and array protocol
- Chaco - a scientific plotting layer on top of Enable optimized for interactive 2D visualization.
- Scatterplots and lineplots
- Image plots
- Mayavi - a 3D visualization framework built on top of VTK and Traits